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undergraduate programs (BS through PhD). The College has seven academic programs that are externally accredited and is home to more than 1,900 undergraduate and 950 graduate students and approximately 140 faculty
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researchers and graduate students. Required Knowledge, Skills and Abilities AI/ML Expertise: Strong knowledge of advanced machine learning, deep learning, and AI techniques. Programming Skills: Proficiency in
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topics ranging across programming language (especially Bayesian statistical probabilistic programming), statistical machine learning, generative AI, and AI Safety. Key Responsibilities: Manage own academic
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machine learning techniques to enhance source detection sensitivity. Multimessenger modelling and interpretation of Galactic sources. This position offers the opportunity to work at the forefront
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be disseminated through academic publications and online webinars. The successful candidate will have a PhD in human-computer interactions or computer science and related fields, with demonstrable
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in this position will conduct/lead applied as well as fundamental research in physics-informed Artificial Intelligence (AI) and Machine Learning (ML) methodologies enabling digital twin functionalities
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and graduate students in disciplines relevant to chemical risk assessment (e.g., toxicology, chemistry, endocrinology, AI/machine learning) and governmental staff presently involved in chemical risk
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interest in methods development Experience in one or more of the following areas: algorithms development, transcriptome analysis, RNA modifications, statistics, machine learning, long read RNA-Sequencing
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data science, machine learning preferred. - Strong programming skills in R and/or Python required. We invite applications from qualified candidates who share our commitment to employment equity and
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deterministic PDEs and equations subject to stochastic perturbations, integrating approaches from machine learning algorithms, transport theory, and optimization. Examples of relevant equations include, but